Date and Time: November 5th, 2018, 2:30 - 4:00 pm

Room: Meeting Room, 1st floor, Dongliuzhai (Old Campus)

 

Abstract

I show that, under common parameter values, a standard New-Keynesian model with standard search and matching frictions and Nash bargaining accounts significantly well for almost all key business cycle properties of the relevant U.S. macroeconomic variables, including relative standard deviations, autocorrelations, and correlations with output. In addition to its ability to explain the dynamics of inflation and persistent effects of monetary shocks, the model can produce exact cross correlations of the three central aggregate labor variables-unemployment, labor market tightness, and vacancies- as seen in the data. What accounts most for the success of the model is a low value for vacancy costs to GDP ratio, that is equivalent to having a high value for what Ljungqvist and Sargent (AER, 2017) call the inverse of the fundamental surplus fraction, and is inextricable from it. However, in contrast to what Ljungqvist and Sargent suggest that the fundamental surplus fraction is the single intermediate channel through which economic forces generating a high elasticity of market tightness with respect to productivity, I show that the fundamental surplus fraction (or the vacancy cost-GDP ratio) can be at their lowest possible values in the steady state, but the model doesn't generate enough volatility in unemployment if the steady state rate of unemployment is very high. Another contribution of the paper is to demonstrate that how wage inertia emerges as an internal feature of the standard matching model (due to the free-entry condition in vacancy creation) if one wants to have high volatility in unemployment. In other words, due to the nature of the model, there is a trade-off between wage volatility and unemployment volatility. However, this trade-off doesn't necessary emerge in the presence of a labor tax.

Date and Time: June 15th, 2018, 4:00 - 5:30 pm

Room: A 101 in the Economics Building (Museum)

 

Abstract

This paper analyses the effect of inter provincial market segmentation on the survival time of enterprises with Chinese industrial enterprises data using the Cox proportional hazards model. The results show that: (1) There is an U relationship between market segmentation and enterprise survival time. Minor market segmentation is helpful to improve the enterprise's survival time, while stronger market segmentation will reduce the company's survival time. (2) Market segmentation reduces the survival time of enterprises by two mechanisms, reducing productivity and weakening innovation incentives. (3) Specially, we further investigated the effect of market segmentation on different ownership enterprises. Market segmentation will significantly improve the survival time of state-owned enterprises, and shorten the survival time of private enterprises.

Date and Time: May 18th, 2018, 4:00 - 5:30 pm

Room: A 101 in the Economics Building (Museum) on New Campus

Abstract

In this paper we reexamine the literature on money demand in China published both in English and Chinese language. Over the past 30 years - starting with the paper by Chow (1987) there has been a regular stream of papers assessing the Chinese money demand function. The literature is mostly focusing on income elasticity, stability, and - which is special for China - the adequate choice and quality of data. In particular regarding stability of money demand, we find a substantial publication bias towards rejecting stability. When controlling for publication bias, and focusing on longer time periods, our paper strongly suggests stable long run money demand in China.

Date and Time: May 4th, 2018, 2:30 - 4:00 pm

Room: A 101 in the Economics Building (Museum)

Abstract

Soybean is one of the main imported US products of China, which has been accounting for around 10% of the total imports from the US since 2008. The recent trade tension between the US and China has made soybeans get much attention as the soybean fell into the first list of products which were imposed 25% retaliation tariff. This paper investigates the possible effects of such a tariff increase through the effects of soybean import price shock on Chinese edible oil price, pork price as well as CPI. The impulse responses of our structural vector autoregressive models show that around 30% of the increase in soybean import price can be transmitted to Chi-
nese domestic edible oil price while very little can be transmitted to pork price. About 3% of the soybean import price shock can be passed onto CPI. Our study shed light on the possible negative effects of the increased the US soybean tariffs on the Chinese economy. At the same time, we also clarify the channel that the transmit the soybean import price shock to CPI is edible oil instead of
pork.

Date and Time: April 20th, 2018, 2:30 pm - 4:00 pm

Room: A 101 in the Economics Building (Museum) on New Campus